The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
Modern military aircraft require a capability to target precision-guided weapons. One method to do this is to use sensor images obtained by sensors carried on the aircraft. However, making an on-board sensor highly accurate so that targets can be located within a ground coordinate system with sufficient accuracy is difficult and expensive. These problems can be overcome by registering the sensor image with a predefined, geographically aligned image obtained from a reference image database. When image registration is done with sufficient accuracy, the geographic alignment of the reference image can be applied to the sensor image, to thus obtain sufficient geographic accuracy for target points selected from the sensor image.
As can be appreciated, image registration can be applicable to various systems employing image recognition. In some instances additional confirmation of the validity and accuracy of the registration process may be required. Such is the case with weapon targeting systems as discussed above or with aircraft navigation systems. Such may also be the case with automated inspection systems where errors in the registration process could cause substantial damage to operations or to system components. Systems employing a manual registration process may also suffer unseen errors, and could similarly benefit from a method to confirm the validity and accuracy of the registration process.
Registration quality confirmation has conventionally been achieved by statistical measures applied to control points, identified and measured in the two images. The statistical measures are most commonly performed for manual registration. Measurement of such control point sets can be tedious. Interpretation of the results, while statistically useful, is still a statistical process and not necessarily an indication of validity or accuracy at arbitrary points in the images. In addition, confirming the quality of the registration process can be difficult due to the difference in visual appearance of the two images. For example, the two images may be from different sensors, or be from a similar sensor but at a different time, or even be from the same sensor but from a different point of view. In each instance, the differences in appearance are enough to lower the certainty or accuracy of any registration attempt.